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Restricted bayes strategies for convex stochastic programs

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Abstract

Generally it is assumed that the joint probability distribution of the random variables involved in a stochastic program is known. In practice however the knowledge of this distribution is only partial. This paper is concerned with convex stochastic programs with partial information, where the confidence in this joint probability distribution is expressed by a parameter varying from 0 to 1. It is shown that in certain cases a program with simple recourse where one is placed in such a situation of partial information reduces to a program of the same type but where the joint probability distribution of the random variables involved is known. The possibility of solving such programs is also indicated.

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Authors and Affiliations

  1. Department of Operations and Decision Systems and Department of Mathematics, Laval University, GIK 7P4, Quebec, Que., Canada

    Raymond Nadeau & Radu Theodorescu

Authors
  1. Raymond Nadeau
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  2. Radu Theodorescu
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Additional information

This research was supported by the Natural Sciences and Engineering Research Council Canada Grant A-7223 and by the Québec Action Concertée Grant EQ-1023.

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Nadeau, R., Theodorescu, R. Restricted bayes strategies for convex stochastic programs. Rend. Circ. Mat. Palermo 33, 109–116 (1984). https://doi.org/10.1007/BF02844415

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  • DOI: https://doi.org/10.1007/BF02844415

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